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Why Should Practitioners be Concerned about Predictive Uncertainty of Groundwater Management Models?

Overview of attention for article published in Water Resources Management, October 2016
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Mentioned by

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1 X user

Citations

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29 Dimensions

Readers on

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67 Mendeley
Title
Why Should Practitioners be Concerned about Predictive Uncertainty of Groundwater Management Models?
Published in
Water Resources Management, October 2016
DOI 10.1007/s11269-016-1508-2
Authors

H. Delottier, A. Pryet, A. Dupuy

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 1%
Portugal 1 1%
Canada 1 1%
Unknown 64 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 33%
Student > Master 8 12%
Student > Doctoral Student 7 10%
Researcher 6 9%
Professor 4 6%
Other 9 13%
Unknown 11 16%
Readers by discipline Count As %
Earth and Planetary Sciences 17 25%
Engineering 13 19%
Environmental Science 11 16%
Physics and Astronomy 2 3%
Agricultural and Biological Sciences 1 1%
Other 5 7%
Unknown 18 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 February 2017.
All research outputs
#20,403,545
of 22,953,506 outputs
Outputs from Water Resources Management
#526
of 617 outputs
Outputs of similar age
#277,439
of 320,409 outputs
Outputs of similar age from Water Resources Management
#12
of 25 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 617 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 320,409 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.